From Prototype to Classroom: An Intelligent Tutoring System for Quantum Education

2026-04-27

AI Summary

This study addresses the challenges of teaching quantum computing in resource-constrained institutions, where counterintuitive concepts, mathematical complexity, and a shortage of qualified instructors hinder effective instruction. To overcome these barriers, this work proposes ITAS—an intelligent tutoring system built on a multi-agent architecture that innovatively integrates Watrous’s quantum information pedagogical framework, a knowledge graph–enhanced large language model, and cloud-native deployment to enable dynamic instruction, adaptive course planning, and learning analytics. Deployed successfully in a real classroom at Old Dominion University, ITAS demonstrates that agent specialization mitigates task-boundary failures, supports class-scale concurrent access at a cost lower than traditional textbooks, and empowers instructors to uncover latent curricular gaps through its dialogue analysis layer.

Abstract

Quantum computing instructors face a compounding problem: the concepts are counterintuitive, the mathematical formalism is dense, and qualified faculty are scarce outside a small number of well-resourced institutions. Our prior work introduced a knowledge-graph-augmented tutoring prototype with two specialized LLM agents: a Teaching Agent for dynamic interaction and a Lesson Planning Agent for lesson generation. Validated on simulated runs rather than in a real course, that prototype left open whether more aggressive agent specialization would be needed to handle the full range of quantum education tasks under real student load. This paper answers the three questions that the prototype could not answer. Can agent specialization solve the reliability problem in a domain as technically demanding as quantum information science? Can the system run in a real course, not a demonstration? Does the instructor gain actionable intelligence from the deployment? We present ITAS (Intelligent Teaching Assistant System), a multi-agent tutoring system built around four contributions: a five-module QIS curriculum grounded in Watrous's information-first framework, a Spoke-and-Wheel teaching architecture with quantum-specialized agents, a cloud infrastructure designed for production use and regulatory compliance, and a conversational analytics layer for instructors and content developers. Piloted in a quantum computing course at Old Dominion University, the system supports all three answers: deployment evidence is consistent with specialization addressing the task-boundary failures observed in the prototype, cloud infrastructure supports classroom-scale concurrency at sub-textbook cost, and the analytics agent surfaces curriculum gaps the instructor could not otherwise see.

Problem

• quantum education
• intelligent tutoring system
• agent specialization
• classroom deployment
• teaching reliability

Innovation

• multi-agent tutoring system
• quantum education
• agent specialization
• conversational analytics
• cloud-based educational infrastructure